Comparative analysis of clinical and immunological profiles across Omicron BA.5.2 subvariants using next-generation sequencing in a Chinese cohort

Objective The Omicron BA.5.2 variant of SARS-CoV-2 has undergone several evolutionary adaptations, leading to multiple subvariants. Rapid and accurate characterization of these subvariants is essential for effective treatment, particularly in critically ill patients. This study leverages Next-Generation Sequencing (NGS) to elucidate the clinical and immunological features across different Omicron BA.5.2 subvariants. Methods We enrolled 28 patients infected with the Omicron variant, hospitalized in Zhangjiajie People’s Hospital, Hunan, China, between January 20, 2023, and March 31, 2023. Throat swabs were collected upon admission for NGS-based identification of Omicron subvariants. Clinical data, including qSOFA scores and key laboratory tests, were collated. A detailed analysis of lymphocyte subsets was conducted to ascertain the extent of immune cell damage and disease severity. Results Patients were infected with various Omicron subvariants, including BA.5.2.48, BA.5.2.49, BA.5.2.6, BF.7.14, DY.1, DY.2, DY.3, and DY.4. Despite having 43 identical mutation sites, each subvariant exhibited unique marker mutations. Critically ill patients demonstrated significant depletion in total lymphocyte count, T cells, CD4, CD8, B cells, and NK cells (P < 0.05). However, there were no significant differences in clinical and immunological markers across the subvariants. Conclusion This study reveals that critically ill patients infected with different Omicron BA.5.2 subvariants experience similar levels of cellular immune dysfunction and inflammatory response. Four mutations - ORF1a:K3353R, ORF1a:L3667F, ORF1b:S997P, S:T883I showed correlation with immunological responses although this conclusion suffers from the small sample size. Our findings underscore the utility of NGS in the comprehensive assessment of infectious diseases, contributing to more effective clinical decision-making.


Introduction
Since the discovery of the 'coronavirus disease 2019'  towards the end of 2019, the novel coronavirus (SARS-CoV-2) has continued to evolve and has given rise to mutant strains such as Alpha, Beta, Gamma, Delta, Lambda, and Omicron.Currently the Omicron strain is predominant all over the world.Compared to the previous strains such as Alpha and Delta, Omicron appears to cause less severe clinical symptoms and is more likely to infect the upper respiratory tract.As a result, the proportion of severe cases, hospitalizations, and mortality rates have decreased (Sievers et al., 2022).However, the Omicron strain's infectivity and immune evasion continue to increase as a considerable number of mutations in the S protein (Polatoglu et al., 2023).On November 26, 2021, the WHO classified it as a variant of concern (VOC).
The genome sequences of the SARS-CoV-2 detected in China between September 26, 2022 and April 13, 2023 were all Omicron variants, covering 106 evolutionary branches, with the most prevalent strains being BF.7.14, DY.2, DY.4,BA.5.2.48, and DY.1, DY.3 (Chinese Center for Disease Control and Prevention).BA.5.2 was caused by the mutation BA.5+ORF9b:D16G;BA.5.2.48, BF.7.14, and DY variants were derived from BA.5.2, containing novel mutation sites S:A57S, ORF1a:T1788M, and S:C124F.Virus mutations often result in modifications to the disease manifestation, symptoms, and defining characteristics.Previously it was assumed that BA.5.2.48 strain and BF.7 strain might be different in their ability to cause disease, however, A comprehensive search was conducted on Web of Science, PubMed, and China National Knowledge Infrastructure to identify relevant literature on Omicron BA.5.2 subvariants.limited studies were found on the clinical characteristics of BA.5.2.48,BA.5.2.49,and BF.7.14.until now no report is available to describe the clinical features of the DY subvariant.
T lymphocytes were discovered to be crucial in the process of the novel corona virus's resistance (Toor et al., 2020;Tirelli et al., 2023).Despite a significant number of mutations in the virus, the Omicron strain is still attacked by the T cell immune response.However, patients with severe COVID-19 frequently have a cytokine storm, which results in excessive T cell activation and exhaustion, a large number of T cells being destroyed, and patients could die from immune function failure.It is currently unclear, nevertheless, if distinct Omicron variants (BA.5.2 evolutionary strains) could produce different harm to human immune function.In this study, the nucleic acids were extracted from the throat swabs of all enrolled patients and sequenced to determine the type of variation.General patient data and laboratory examination (including lymphocyte subsets, etc.) data were collected to investigate the relationship between subvariants of Omicron BA.5.2.and clinical characteristics, immune function, and disease severity.

Study participants
The present study was an observational study of patients with SARS-CoV-2 infection were admitted to Zhangjiajie People's Hospital (Hunan, China) between January 20, 2023, andMarch 31, 2023 were included in this study.All patients met the diagnosis criteria of SARS-CoV-2 infection, as outlined in the National Health Commission of China's Trial Ninth Edition (National Health Commission State Administration of Traditional Chinese Medicine, 2022).Patients were excluded if they had following conditions:1).Patients with severe immunodeficiency such as HIV, end-stage tumors, and long-term use of immunosuppressants; 2).The quality of samples did not meet the detection standards (such as nucleic acid PCR CT value >32, etc.); 3).Patients who cannot cooperate to complete the sample collection; 4).Patients who did not have sufficient clinical data; 5).Patients who refuse to participate in this study.A total of 28 people were included in this study (Supplementary Figure 1), including 10 patients with severe COVID-19 (clinically diagnosed as severe or critical) and 18 non-severe patients (clinically diagnosed as mild or moderate).(Supplementary Table 1).This study was approved by the Medical Ethics Review Committee of Zhangjiajie People's Hospital (IRB-2022237), and all patients signed informed consent.

Data and sample collection
Throat swabs were collected from enrolled patients to detect and identify the Omicron subvariants.The collected samples were stored in a -20°C refrigerator with RNA preservation solution for a short period of time to maintain the integrity of nucleic acids and prevent degradation.Upon admission, the patient's general health was thoroughly reviewed, other information of underlying diseases, potential complications, and clinical symptoms was gathered.Additionally, the qSOFA score and laboratory tests, including lymphocyte subsets, were assessed to reflect the patient's immune function.The qSOFA score is a tool used to evaluate the risk of sepsis in patients.The score is calculated based on three criteria: systolic blood pressure of 100 mmHg or lower, shortness of breath of 22 breaths per minute or more, and mental status changes.Each criterion is worth one point, and a score of 2 or higher indicates a high likelihood of sepsis and requires close monitoring (Song et al., 2018).

Flow cytometric analysis
Peripheral blood lymphocytes were detected using a flow cytometer called BriCyte E6, which was purchased from China Mindray Biomedical Electronics Co., Ltd.The flow cytometer collected parameter information such as forward scattered light (FSC), side scattered light (SSC), and fluorescence signals of cells.It then analyzed the subpopulations of T lymphocytes (CD3 + ), the auxiliary/inducible classification and counting of T lymphocytes (CD3 + CD4 + ), the suppressor/cytotoxic T lymphocytes (CD3 + CD8 + ) subpopulation, the B lymphocytes (CD3 -CD19 + ) and NK cells (CD3 -CD16 + CD56 + ).The reagents used consisted of a four-color reagent for CD3-FITC/CD8-PE/CD45-PerCP/CD4-APC and another four-color reagent for CD3-FITC/CD16 + 56-PE/CD45-PerCP/CD19-APC. All tests were performed strictly following the instructions and standard operating procedures provided with the kit to ensure accurate test results.

Sequencing and mutation analysis of Omicron subvariants
RNAs were extracted from the 300 µL of samples of throat swabs using a QIAamp Viral RNA Mini Kit.The cDNA synthesis, SARS-CoV-2 sequence enrichment, library amplification, and indexing were performed by using the SARS-CoV-2 Nucleic Acid Diagnosis Kit (Sequencing by Reversible Termination, Sansure Biotech, China).An elution volume of 20-50 mL for each RNA sample was used for cDNA synthesis.After the cDNA reaction, A multiplex PCR reaction was done to amplify the entire SARS-CoV-2 genome using specifically designed primers.The product DNA was diluted to approximately 0.5 ng/mL and 1 ng of DNA was added to the reaction system for DNA fragmentation and library construction.After the reaction was completed, it was purified using 80% fresh ethanol and DNA Clean Beads.The quality of the library was analyzed using the LabChip GX Touch ™ DNA 1K Chip ® .Next-generation sequencing was done by using SE150 of GeneMind's sequencer (SansureSeq1000, China), at least 8M reads were obtained for each sample.All the sequencing data (FastQ files) of samples can be downloaded from cncb.ac.cn with accession number PRJCA019496.
Low quality and adapter sequences were removed using trim_galore, more than 99% of the remaining raw reads (so-called clean reads) were used for analysis.More than 98% of the clean reads could be mapped to the SARS-CoV-2 reference genome Wuhan-Hu-1 (NC_045512.2) using Burrows-Wheeler Alignment tool (BWA-MEM v0.7.17).Subsequently, the mapped reads were assembled into a consensus sequence using samtools (v1.9) and ivar (v1.2.1) tools, and the sites whose depth is lower than the threshold parameter (20x) will be output as N.For phylogenetic analysis, full-length SARS-CoV-2 reference sequences were selected according to the categories of novel coronavirus labels in GISAID database, in which 2 reference sequences were selected respectively from 10 categories: Alpha, Beta, Gamma, Delta, Epsilon, Zeta, Eta, Theta, Iota and Kappa, and the patient's consensus sequences were classified into lineages using PANGOLIN and into clades using NextClade (v0.10.0).Multi-sequence alignment was performed with MAFFT (v7.271),FastTee was used to construct phylogenetic tree.The mutation frequency of the site was calculated by VarScan (v2.4.4).

Statistical analysis
Measurement data were described by median (interquartile range), Count data were expressed as frequencies with percentages.Comparative analysis between groups was conducted using Kruskall, Mann-Whitney non-parametric rank sum test, Fisher chi-square test and Wilcoxon test.All statistical analyses were performed using SPSS 22.0, and a P value less than 0.05 was considered statistically significant.

Laboratory findings and lymphocytes subsets detection
The lymphocyte counts were found to decline in patients, and the levels of C-reactive protein, interleukin-6, procalcitonin, D- Lymphocyte subsets were used to assess a patient's immune system.In patients with Omicron infection, total T lymphocyte count, CD4 + lymphocyte count, CD8 + lymphocyte count, B lymphocyte count, and NK cell count were all below normal values, only the corresponding percentage and CD4 + /CD8 + ratio were essentially within the normal range (Table 3).

Relationship between disease severity and lymphocyte subsets
We categorized all patients as severe or non-severe Omicron infection.Total 18 of them had non-severe conditions, while 10 had  The consensus sequences of 28 SARS-CoV-2 samples were obtained with the sequence length ranging from 29842 to 29854bp.The average sequencing depth was 32200x and the genome average coverage of sequencing was 99%.The NextClade analysis showed that the 28 SARS-CoV-2 sequences belonged to 22B (Omicron); With Pangolin typing, the subvariants were classified 5 to Omicron BA.5.2, 8 to Omicron BF.7, 1 to Omicron DY.1, 4 to Omicron DY.2, 5 to Omicron DY.3, 5 to Omicron DY.4.An evolutionary tree was built based on the complete genome sequences of COVID-19 samples.We calculated a maximumlikelihood phylogeny, including all SARS-CoV-2 genomes of interest, genomes of viruses from patients in this study were shown in red.The patients phylogenetic tree showed 3 defined clusters BF, DY and DZ (Figure 2).The Pangolin typing with different depth threshold (20X, 100X) showed consistent classification results.
Patients with Omicron subvariants (BA.5.2.48+BA.5.2.49+BA.5.2.6), BF.7.14 and DY subvariants all had reduced lymphocyte counts and the levels of CRP, IL-6, PCT, DDT, and troponin were all higher than normal (Table 2).total lymphocyte counts, total T lymphocyte counts, NK cell counts, were all lower than normal.There was no statistical significance between the groups for most parameters (P>0.05)except Leukocyte and Neutrophils with P value of 0.002 and 0.009 (Table 2); there was also no significant difference in the PCR CT values between groups (Table 3).
Box plots comparing the three subvariant groups for numerical laboratory testing results are shown in Figure 4. Wilcoxon p values are labeled for each comparison, which are consistent with the p values in Tables 1-3.

Correlation between mutation sites and immunological parameters
For the 86 specific mutations in the consensus sequences of 28 samples, we selected 23 of them which has at least 3 samples with mutation or non-mutation.Spearman Rank Correlation was performed between the mutations (1 representing mutation and 0 representing non-mutation) and the laboratory testing parameters.A heatmap of Spearman correlation coefficients between the mutations and testing parameters is displayed in Figure 5. 20 pairs of mutations and testing parameters are selected with Spearman correlation coefficient greater than 0.5, which include 8 specific mutations.Box plots comparing the mutation and nonmutation groups for the selected pairs are illustrated in Figure 6.Wilcoxon test p values are labeled for each comparison, which showed statistical significance(P<0.05).Four mutations -ORF1a: K3353R, ORF1a:L3667F, ORF1b:S997P, S:T883I showed consistent correlation with four parameters: CRP, Leukocyte, Neutrophils, Phylogenetic tree of SARS-CoV-2 genomes representing strains and subvariants from the patients (in red).

Discussion
Currently, the Omicron BA.5.2 subvariant is getting rampant in China and there are numerous studies available concerned with Omicron.However, there are no articles examining whether there are differences between clinical features, immune function, and disease severity among BA.5.2 subvariants (BA.5.2.48, BA.5.2.49, BF.7.14 and DY).Our study aims to fill this gap in knowledge.
SARS-CoV-2 attaches to the ACE2 receptor via the receptorbinding domain (RBD) on its surface, and then invades the host cells.The peripheral blood lymphocytes have been found to decrease significantly in patients with severe COVID-19 infections.Recent studies found SARS-CoV-2 potentially attacked and destroyed T lymphocytes, similar to the way human immunodeficiency virus (HIV) operates.It resulted in a decline or failure of the immune function, and in severe cases, even lead to the death of patients (Jafarzadeh et al., 2021).The severity and prognosis of the clinical condition were correlated with T cell destruction and immune response (Huang et al., 2020).However, ACE2 receptors are rarely present on the surface of T lymphocytes.It was speculated that SARS-COV-2 may bind to the CD147 receptors or integrins on the surface of T lymphocytes (Kuklina, 2022;Huang et al., 2023), leading to their invasion and subsequent destruction.This can result in a significant decrease of T lymphocyte count in the bloodstream.In present study, we found that the total lymphocyte counts, total T lymphocyte counts, CD4 cell counts, CD8 cell counts, B cell counts, and NK cell counts in patients with Omicron infection were significantly lower than normal.Compared to non-critically ill patients, critically ill patients exhibited higher levels of IL-6 and might subject to more severe cellular immunity attacks, and the level of lymphocytes decreases significantly, which was consistent with the findings of early research conducted by Liu et al (Liu et al., 2020;Liu et al., 2021).This phenomenon may be related to the hyperactivation of inflammatory factors and the excessive activation and abnormal apoptosis of lymphocytes.However, Our study found no significant difference in the lymphocyte subsets among the BA.5.2 evolutionary strains of Omicron, although all strains showed lower lymphocyte counts than normal.It may indicate that BA.5.2 evolutionary strains have roughly the same affinity and attack power toward lymphocytes, In addition, there was no significant difference in nucleic acid PCR CT values of all patients, which was consistent with the study by Shi et al (Yin et al., 2021).suggesting that their Box plots comparing the three subvariant groups for numerical laboratory testing results.viral loads were similar, and viral load was not a reliable indicator for distinguishing disease severity and different subvariants of the Omicron.
The clinical manifestations of most patients were similar to those reported in previous studies (Huang et al., 2020).The most common symptoms on admission were fever, cough, expectoration, shortness of breath, sore throat and headache.Previous studies have identified various risk factors that were closely associated with the prognosis of patients (Shi et al., 2020;Zhou et al., 2020).These included an increase in neutrophil counts, a decrease in lymphocyte counts, higher levels of inflammatory factors such as CRP and IL-6, increased troponin, creatinine and DDT levels, as well as a higher qSOFA score.In our study, the lymphocyte counts of patients have decreased, and the levels of C-reactive protein, IL-6, procalcitonin, D-dimer, troponin, were higher than normal values.Undoubtedly, these laboratory indicators often indicate the severity of the disease, as they reflect a hyperactivation of inflammatory factors within the patient's body, which can even result in multiple organ dysfunction.Therefore, clinicians need to be highly vigilant when the above indicators change.Furthermore, it has been observed that critically ill patients exhibit significantly higher qSOFA scores (p<0.001).It is important to note that the severity of organ function damage is directly proportional to the qSOFA score, indicating a higher likelihood of sepsis and septic shock.Consequently, patients with these characteristics tend to have a poorer prognosis.Previous reports have indicated that BA.5.2.48 is more likely to result in severe diseases and has a higher proportion of severe cases compared to BF.7 (Wang et al., 2023).However, our study found no significant differences in laboratory tests and qSOFA scores between different evolutionary strains of Omicron BA.5.2.Additionally, the proportion of patients with severe Omicron infection was similar across different subvariants, indicating that the disease severity and prognosis resulted by each evolutionary strain of Omicron BA.5.2 were analogical.
Mutations in the N-terminal domain (NTD) of the spike protein can alter the antigen structure of Omicron.Additionally, mutations in the RBD have been found to enhance the affinity of the virus for the human ACE2 receptors (Wang et al., 2023).The mutations can increase the infectiousness and immune escape of Omicron significantly.In this study, genomic sequences and mutation sites of viruses were identified in all patients, revealing 43 identical mutation sites across all samples, which were consistent with known mutation sites of the Omicron subvariants.We also found that specific mutations were present in different samples.The ORF9b:V30L, ORF9b:A29I, ORF7a:H47Y, and N:S33F mutations were exclusively found in the BF.7.14 sample.Similarly, S:N1125S, Heatmap of Spearman correlation coefficients between specific mutation sites and immunological parameters.
S:A570S, ORF7a:F63H, ORF1b:Y1648C, ORF1b:I2664V, ORF1a: T2967I, ORF1a:L3352F, and ORF1a:L3116F mutations were only present in the DY.1 samples.The N:Q241K mutation was exclusive to the DY.2 sample, while the ORF1a:T1788M mutation was found only in the DY.3 sample.And the ORF1b:T2432I, ORF1a:T4175I, ORF1a:T1840I and ORF1a:S3949N mutations were exclusively present in the DY.4 samples.We found there was no statistical significance between the three subvariant groups for most parameters (P>0.05)except Leukocyte and Neutrophils.Four mutations -ORF1a:K3353R, ORF1a:L3667F, ORF1b:S997P, S: T883I showed correlation with four parameters: CRP, Leukocyte, Neutrophils, Total T cell count, and there was no knowledge found about these four mutations.Another four mutations -ORF1a: S3949N, ORF1a:T1840I, ORF1a:T4175I, ORF1a:T1788M showed correlation with Hemoglobin or ALT only, and they only exist in DY.4 samples.This study is limited by the lack of B lymphocyte percentage and count, as well as NK cell percentage and count in certain patients with the DY subvariant, meant that the immune function of these patients cannot be fully displayed.Additionally, the study has a small sample size, with only 28 patients with Omicron infection included, and it would be more persuasive if the sample was larger.

Conclusions
As far as we know, there are few articles discussing the various evolutionary branches of Omicron BA.5.2. it would assume that there were differences in clinical characteristics and disease severity among the evolutionary branches of Omicron BA.5.2, but the evidence is insufficient.Our study analyzed the genomic sequences of Omicron viruses from all enrolled patients, and Boxplots comparing the mutation and non-mutation groups for the selected mutation sites and immunological parameters with Spearman correlation coefficient greater than 0.5.explored whether there were differences in clinical characteristics, immune function, and disease severity among Omicron BA.5.2 subvariants.Four mutations -ORF1a:K3353R, ORF1a:L3667F, ORF1b:S997P, S:T883I showed correlation with immunological responses although this conclusion suffers from the small sample size.In our study, the clinical characteristics, immune function damage, and disease severity of different subvariants of Omicron BA.5.2 appeared to be similar.However, we found that critically ill patients experienced a more severe cellular immune attack and inflammatory response.In conclusion, this study presented clinical characteristics of Omicron subvariants infection in COV-19 patients and systematically analyzed important lymphocytes subsets in each clinical subgroup.It would help clinician to better management of Omicron infections in future.

FIGURE 3
FIGURE 3Hierarchical classification heatmap of SARS-CoV-2 specific mutations (in black) representing strains and subvariants from the patients (in color).

TABLE 1
General information and clinical characteristics.

TABLE 2
Laboratory findings and qSOFA score.

TABLE 3
Lymphocyte subsets and CT value of the nucleic acid.

TABLE 4
Lymphocyte subsets, IL-6 and PCR CT value of the nucleic acid.